FlexGP
We describe FlexGP, the first Genetic Programming system to perform symbolic regression on large-scale datasets on the cloud via massive data-parallel ensemble learning. FlexGP provides a decentralized, fault tolerant parallelization framework that runs many copies of Multiple Regression Genetic Pro...
Main Authors: | Veeramachaneni, Kalyan, Arnaldo, Ignacio, Derby, Owen, O’Reilly, Una-May |
---|---|
Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | English |
Published: |
Springer Netherlands
2016
|
Online Access: | http://hdl.handle.net/1721.1/103516 |
Similar Items
-
FlexGP : a scalable system for factored learning in the cloud
by: Derby, Owen C
Published: (2014) -
FlexGP 2.0 : multiple levels of parallelism in distributed machine learning via genetic programming
by: Sherry, Dylan J. (Dylan Jacob)
Published: (2014) -
Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization
by: Vladislavleva, Ekaterina, et al.
Published: (2016) -
OpenTuner: An Extensible Framework for Program Autotuning
by: Ansel, Jason, et al.
Published: (2013) -
Autotuning Algorithmic Choice for Input Sensitivity
by: Ding, Yufei, et al.
Published: (2014)